****************************************************************************
* File-Name: 		mexicocodes.do
* Date:		 02/18/2020
* Author: 		Fred Batista
* Purpose: 		Analysis of Mexico experiment
* Data used: 		mexicodata.dta
* Data Output:	None	*/
****************************************************************************


* balance checks (control for gender and ideology)

mlogit condition age2 education woman approval2 left center right religiosity white mestizo single children i.region, base(2)

* priming answers to sexism

reg manmorecorrupt i.primed##i.female_inc##i.corruption age2 education woman approval2 left center right religiosity white mestizo single children i.region

reg womenpurity i.primed##i.female_inc##i.corruption age2 education woman approval2 left center right religiosity white mestizo single children i.region

reg menbetterleaders i.primed##i.female_inc##i.corruption age2 education woman approval2 right center left religiosity white mestizo single children i.region

test (primed=0) (female_inc=0) (corruption=0) (c.primed#c.female_inc=0) (c.primed#c.corruption=0) (c.female_inc#c.corruption=0) (c.primed#c.female_inc#c.corruption=0), mtest(h)

*margins, at(primed=(0(1)1) female_inc=(0(1)1) corruption=(0(1)1))

*marginsplot, x(primed female_inc corruption) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle("Predicted Hostile Sexism", height(7)) xtitle(" ") xlabel(0.5 " " 1 `" "Treated" "Honest" "Male" "' 2 `" "Treated" "Corrupt" "Male" "' 3 `" "Treated" "Honest" "Female" "' 4 `" "Treated" "Corrupt" "Female" "' 5 `" "Baseline" "Honest" "Male" "' 6 `" "Baseline" "Corrupt" "Male" "' 7 `" "Baseline" "Honest" "Female" "' 8 `" "Baseline" "Corrupt" "Female" "' 8.5 " ", noticks labsize(medsmall)) ylabel(.3(.05).5,nogrid) title("Mexico", color(black) size(vlarge)) yscale(noextend)  plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(12)

* or

grstyle init

grstyle color background white

*marginsplot, x(female_inc corruption) subtitle(,fcolor(white) bcolor(white)) bydimension(primed, lab("TREATED" "NOT TREATED", labsize(9))) byopts(title(Mexico: Predicted Hostile Sexism)) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle(" ") xtitle(" ") xlabel(0.5 " " 1 `" "Honest" "Male" "Politician" "' 2 `" "Corrupt" "Male" "Politician" "' 3 `" "Honest" "Female" "Politician" "' 4 `" "Corrupt" "Female" "Politician" "' 4.5 " ", noticks labsize(medsmall)) ylabel(.3(.05).5,nogrid) title(" ") yscale(noextend)  plotregion(style(none)) plotregion(fcolor(white)) graphregion(fcolor(white)) ysize(8) xsize(12)

grstyle init

grstyle color background white

margins, at(primed=(0) female_inc=(0(1)1) corruption=(0(1)1))

marginsplot, x(female_inc corruption) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle("Predicted Hostile Sexism") xtitle(" ") xlabel(0.5 " " 1 `" "Honest" "Male" "Politician" "' 2 `" "Corrupt" "Male" "Politician" "' 3 `" "Honest" "Female" "Politician" "' 4 `" "Corrupt" "Female" "Politician" "' 4.5 " ", noticks labsize(medsmall)) ylabel(.3(.05).5,nogrid) title("Treatment Before Moderator") yscale(noextend)  plotregion(style(none)) plotregion(fcolor(white)) graphregion(fcolor(white)) ysize(8) xsize(8) saving(mexnoprimehos)

margins, at(primed=(1) female_inc=(0(1)1) corruption=(0(1)1))

marginsplot, x(female_inc corruption) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle("") xtitle(" ") xlabel(0.5 " " 1 `" "Honest" "Male" "Politician" "' 2 `" "Corrupt" "Male" "Politician" "' 3 `" "Honest" "Female" "Politician" "' 4 `" "Corrupt" "Female" "Politician" "' 4.5 " ", noticks labsize(medsmall)) ylabel(.3(.05).5,nogrid) title("Treatment After Moderator") yscale(noextend)  plotregion(style(none)) plotregion(fcolor(white)) graphregion(fcolor(white)) ysize(8) xsize(8) saving(mexprimehos)

* combining graphs

graph combine mexnoprimehos.gph mexprimehos.gph, ycommon title(Mexico, size(vlarge)) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(14) iscale(1) saving(mexhos)

reg womencontrol i.primed##i.female_inc##i.corruption age2 education woman approval2 left center right religiosity white mestizo single children i.region

reg benevolent c.primed##c.female_inc##c.corruption age2 education woman approval2 right center left religiosity white mestizo single children i.region

test (primed=0) (female_inc=0) (corruption=0) (c.primed#c.female_inc=0) (c.primed#c.corruption=0) (c.female_inc#c.corruption=0) (c.primed#c.female_inc#c.corruption=0), mtest(h)

*margins, at(primed=(0(1)1) female_inc=(0(1)1) corruption=(0(1)1))

*marginsplot, x(primed female_inc corruption) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle("Predicted Benevolent Sexism", height(7)) xtitle(" ") xlabel(0.5 " " 1 `" "Treated" "Honest" "Male" "' 2 `" "Treated" "Corrupt" "Male" "' 3 `" "Treated" "Honest" "Female" "' 4 `" "Treated" "Corrupt" "Female" "' 5 `" "Baseline" "Honest" "Male" "' 6 `" "Baseline" "Corrupt" "Male" "' 7 `" "Baseline" "Honest" "Female" "' 8 `" "Baseline" "Corrupt" "Female" "' 8.5 " ", noticks labsize(medsmall)) ylabel(.3(.05).5,nogrid) title("Mexico", color(black) size(vlarge)) yscale(noextend)  plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(12)

* or

*marginsplot, x(female_inc corruption) subtitle(,fcolor(white) bcolor(white)) bydimension(primed, lab("TREATED" "NOT TREATED", labsize(9))) byopts(title(Mexico: Predicted Benevolent Sexism)) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle(" ") xtitle(" ") xlabel(0.5 " " 1 `" "Honest" "Male" "Politician" "' 2 `" "Corrupt" "Male" "Politician" "' 3 `" "Honest" "Female" "Politician" "' 4 `" "Corrupt" "Female" "Politician" "' 4.5 " ", noticks labsize(medsmall)) ylabel(.3(.05).5,nogrid) title(" ") yscale(noextend)  plotregion(style(none)) plotregion(fcolor(white)) graphregion(fcolor(white)) ysize(8) xsize(12)

margins, at(primed=(0) female_inc=(0(1)1) corruption=(0(1)1))

marginsplot, x(female_inc corruption) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle("Predicted Benevolent Sexism") xtitle(" ") xlabel(0.5 " " 1 `" "Honest" "Male" "Politician" "' 2 `" "Corrupt" "Male" "Politician" "' 3 `" "Honest" "Female" "Politician" "' 4 `" "Corrupt" "Female" "Politician" "' 4.5 " ", noticks labsize(medsmall)) ylabel(.3(.05).5,nogrid) title("Treatment Before Moderator") yscale(noextend)  plotregion(style(none)) plotregion(fcolor(white)) graphregion(fcolor(white)) ysize(8) xsize(8) saving(mexnoprimeben)

margins, at(primed=(1) female_inc=(0(1)1) corruption=(0(1)1))

marginsplot, x(female_inc corruption) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle("") xtitle(" ") xlabel(0.5 " " 1 `" "Honest" "Male" "Politician" "' 2 `" "Corrupt" "Male" "Politician" "' 3 `" "Honest" "Female" "Politician" "' 4 `" "Corrupt" "Female" "Politician" "' 4.5 " ", noticks labsize(medsmall)) ylabel(.3(.05).5,nogrid) title("Treatment After Moderator") yscale(noextend)  plotregion(style(none)) plotregion(fcolor(white)) graphregion(fcolor(white)) ysize(8) xsize(8) saving(mexprimeben)

* combining graphs

graph combine mexnoprimeben.gph mexprimeben.gph, ycommon title(Mexico, size(vlarge)) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(14) iscale(1) saving(mexben)


reg hostile i.primed##i.female_inc##i.corruption age2 education woman approval2 left center right religiosity white mestizo single children i.region



* MODELS WITHOUT MODERATORS (control for sex and ideology)

* full sample

reg trust c.female_inc##c.corruption woman right center left

reg evaluation c.female_inc##c.corruption woman right center left

reg remove c.female_inc##c.corruption woman right center left

reg popularity c.female_inc##c.corruption woman right center left

test (c.female_inc=0) (c.corruption=0) (c.female_inc#c.corruption=0), mtest(h)

margins, dydx(corruption) at(female_inc=(0(1)1))

*margins, at(female_inc=(0(1)1) corruption=(0(1)1))

marginsplot, x(female_inc) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle("Treatment Effect", height(7)) xtitle("") xlabel(-.5 " " 0 `" "Male" "Incumbent" "' 1 `" "Female" "Incumbent" "' 1.5 " ", noticks labsize(large)) ylabel(-.3(.05)-.55,nogrid) title(Mexico, color(black) size(vlarge)) subtitle(Full Sample, size(medlarge) span) yscale(noextend) xscale(noextend)  plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(8) saving(mexmain)

* no controls

reg popularity c.female_inc##c.corruption

* male

reg trust c.female_inc##c.corruption woman right center left if woman==0

reg evaluation c.female_inc##c.corruption woman right center left if woman==0

reg remove c.female_inc##c.corruption woman right center lef if woman==0

reg popularity c.female_inc##c.corruption right center left if woman==0

margins, dydx(corruption) at(female_inc=(0(1)1))

*margins, at(female_inc=(0(1)1) corruption=(0(1)1))

marginsplot, x(female_inc) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle("Treatment Effect", height(7)) xtitle(" ") xlabel(-.5 " " 0 `" "Male" "Incumbent" "' 1 `" "Female" "Incumbent" "' 1.5 " ", noticks labsize(large)) ylabel(-.3(.05)-.55,nogrid) title("Male Subjects", color(black)) yscale(noextend)  plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(8) saving(malesmexnoint)

* female

reg trust c.female_inc##c.corruption woman right center left if woman==1

reg evaluation c.female_inc##c.corruption woman right center left if woman==1

reg remove c.female_inc##c.corruption woman right center lef if woman==1

reg popularity c.female_inc##c.corruption right center left if woman==1

margins, dydx(corruption) at(female_inc=(0(1)1))

*margins, at(female_inc=(0(1)1) corruption=(0(1)1))

marginsplot, x(female_inc) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle("", height(7)) xtitle(" ") xlabel(-.5 " " 0 `" "Male" "Incumbent" "' 1 `" "Female" "Incumbent" "' 1.5 " ", noticks labsize(large)) ylabel(-.3(.05)-.55,nogrid) title("Female Subjects", color(black)) yscale(noextend)  plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(8) saving(femalesmexnoint)

* combining graphs for males and females

graph combine malesmexnoint.gph femalesmexnoint.gph, ycommon title(Mexico, size(vlarge)) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(14) iscale(1) saving(mexgender)

* interaction by gender (not sig)

reg trust c.female_inc##c.corruption##i.woman right center left

reg evaluation c.female_inc##c.corruption##i.woman right center left

reg remove c.female_inc##c.corruption##i.woman right center left

reg popularity c.female_inc##c.corruption##i.woman right center left



** MODELS WITH MODERATORS

* benevolent

* all sample

reg trust c.female_inc##c.corruption##c.benevolent woman right center left

reg evaluation c.female_inc##c.corruption##c.benevolent woman right center left

reg remove c.female_inc##c.corruption##c.benevolent woman right center left

reg popularity c.female_inc##c.corruption##c.benevolent woman right center left

margins, dydx(corruption)  at(female_inc=(0(1)1)  benevolent=(0(.25)1))

power onemean -.0724654 0, n(252) sd(.11)

marginsplot, x(benevolent) plot(female_inc) plot1(mcolor(black) lcolor(black)) plot2(mcolor(gs8) lcolor(gs8)) ci1(lcolor(black) msize(vtiny)) ci2(lcolor(gs8) msize(vtiny)) title("Mexico", color(black) size(vlarge)) subtitle(Full Sample, span) ytitle("Treatment Effect", height(7)) xtitle("Benevolent Sexism", size(medlarge) height(5)) xlabel(0 "0" .25 ".25" .5 ".50" .75 ".75" 1 "1", noticks labsize(medium)) ylabel(, labsize(medium) nogrid) legend(col(2) order(1 "{stSans:Male Politician}" 2 "{stSans:Female Politician}") size(medium) ring(1) row(1)region(lstyle(none)) col(2) colg(7)) yscale(noextend) xscale(noextend) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(8) saving(mexint)

*margins, dydx(corruption) at(female_inc=(0(1)1)  benevolent=(0(1)1))

*marginsplot, plot(female_inc) plot1(mcolor(black) connect(none)) plot2(mcolor(gs8) connect(none)) ci1(lcolor(black) msize(vtiny)) ci2(lcolor(gs8) msize(vtiny)) title("Mexico", color(black) size(vlarge))  ytitle("Average Treatment Effect", height(7)) xtitle(" ") xlabel(-.5 " " 0 `" "Low" "Benevolent" "Sexism" "' 1 `" "High" "Benevolent" "Sexism" "' 1.5 " ", noticks labsize(medium)) ylabel(,nogrid) legend(col(2) order(1 "{stSans:Male Politician}" 2 "{stSans:Female Politician}") size(medium) ring(1) row(1)region(lstyle(none)) col(2) colg(7)) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(8) saving(mexint)

*margins, at(female_inc=(0(1)1) corruption=(0(1)1) benevolent=(0(1)1))

* male

reg trust c.female_inc##c.corruption##c.benevolent right center left if woman==0

reg evaluation c.female_inc##c.corruption##c.benevolent right center left if woman==0

reg remove c.female_inc##c.corruption##c.benevolent right center left if woman==0

reg popularity c.female_inc##c.corruption##c.benevolent right center left if woman==0

margins, dydx(corruption) at(female_inc=(0(1)1)  benevolent=(0(.25)1))

marginsplot, x(benevolent) plot(female_inc) plot1(mcolor(black) lcolor(black)) plot2(mcolor(gs8) lcolor(gs8)) ci1(lcolor(black) msize(vtiny)) ci2(lcolor(gs8) msize(vtiny)) title("Male Subjects", color(black)) ytitle("Treatment Effect", height(9)) xtitle("Benevolent Sexism", size(medlarge) height(5)) xlabel(0 "0" .25 ".25" .5 ".50" .75 ".75" 1 "1", noticks labsize(medium)) ylabel(0(.1)-.7, labsize(medium) nogrid) legend(col(2) order(1 "{stSans:Male Politician}" 2 "{stSans:Female Politician}") size(medium) ring(1) row(1)region(lstyle(none)) col(2) colg(7)) yscale(noextend) xscale(noextend) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(8) saving(malemexint)

*margins, at(female_inc=(0(1)1) corruption=(0(1)1) benevolent=(0(1)1))

* female

reg trust c.female_inc##c.corruption##c.benevolent right center left if woman==1

reg evaluation c.female_inc##c.corruption##c.benevolent right center left if woman==1

reg remove c.female_inc##c.corruption##c.benevolent right center left if woman==1

reg popularity c.female_inc##c.corruption##c.benevolent right center left if woman==1

margins, dydx(corruption) at(female_inc=(0(1)1)  benevolent=(0(.25)1))

marginsplot, x(benevolent) plot(female_inc) plot1(mcolor(black) lcolor(black)) plot2(mcolor(gs8) lcolor(gs8)) ci1(lcolor(black) msize(vtiny)) ci2(lcolor(gs8) msize(vtiny)) title("Female Subjects", color(black)) ytitle("", height(7)) xtitle("Benevolent Sexism", size(medlarge) height(5)) xlabel(0 "0" .25 ".25" .5 ".50" .75 ".75" 1 "1", noticks labsize(medium)) ylabel(0(.1)-.7, labsize(medium) nogrid) legend(col(2) order(1 "{stSans:Male Politician}" 2 "{stSans:Female Politician}") size(medium) ring(1) row(1)region(lstyle(none)) col(2) colg(7)) yscale(noextend) xscale(noextend) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(8) saving(femalemexint)

*margins, at(female_inc=(0(1)1) corruption=(0(1)1) benevolent=(0(1)1))

* combing graphs by gender

graph combine malemexint.gph femalemexint.gph, ycommon title(Mexico, size(vlarge)) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(14) saving(mexgenderint)

* interaction (to test for multiple comparisons

reg popularity c.female_inc##c.corruption##c.benevolent##c.woman right center left

test (female_inc=0) (corruption=0) (benevolent=0) (woman=0) (c.female_inc#c.corruption=0) (c.female_inc#c.benevolent=0) (c.female_inc#c.woman=0) (c.corruption#c.benevolent=0) (c.corruption#c.woman=0) (c.benevolent#c.woman=0) (c.female_inc#c.corruption#c.benevolent=0) (c.female_inc#c.corruption#c.woman=0) (c.female_inc#c.benevolent#c.woman=0) (c.corruption#c.benevolent#c.woman=0) (c.female_inc#c.corruption#c.benevolent#c.woman=0), mtest(h)


* hostile

* all sample

reg trust c.female_inc##c.corruption##c.menbetterleaders woman right center left

reg evaluation c.female_inc##c.corruption##c.menbetterleaders woman right center left

reg remove c.female_inc##c.corruption##c.menbetterleaders woman right center left

reg popularity c.female_inc##c.corruption##c.menbetterleaders woman right center left

margins, dydx(corruption) at(female_inc=(0(1)1)  menbetterleaders=(0(1)1))

margins, at(female_inc=(0(1)1) corruption=(0(1)1) menbetterleaders=(0(1)1))

* male

reg trust c.female_inc##c.corruption##c.menbetterleaders right center left if woman==0

reg evaluation c.female_inc##c.corruption##c.menbetterleaders right center left if woman==0

reg remove c.female_inc##c.corruption##c.menbetterleaders right center left if woman==0

reg popularity c.female_inc##c.corruption##c.menbetterleaders right center left if woman==0

margins, dydx(corruption) at(female_inc=(0(1)1)  menbetterleaders=(0(1)1))

margins, at(female_inc=(0(1)1) corruption=(0(1)1) menbetterleaders=(0(1)1))

* female

reg trust c.female_inc##c.corruption##c.menbetterleaders right center left if woman==1

reg evaluation c.female_inc##c.corruption##c.menbetterleaders right center left if woman==1

reg remove c.female_inc##c.corruption##c.menbetterleaders right center left if woman==1

reg popularity c.female_inc##c.corruption##c.menbetterleaders right center left if woman==1

margins, dydx(corruption) at(female_inc=(0(1)1)  menbetterleaders=(0(1)1))

margins, at(female_inc=(0(1)1) corruption=(0(1)1) menbetterleaders=(0(1)1))


* PRIMING?

* no interaction, full sample

reg trust c.female_inc##c.corruption woman right center left if primed==0

reg evaluation c.female_inc##c.corruption woman right center left if primed==0

reg remove c.female_inc##c.corruption woman right center left if primed==0

reg popularity c.female_inc##c.corruption woman right center left if primed==0

margins, dydx(corruption) at(female_inc=(0(1)1))

marginsplot, x(female_inc) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(tiny)) ytitle("Treatment Effect", height(7)) xtitle(" ") xlabel(-.5 " " 0 `" "Male" "Incumbent" "' 1 `" "Female" "Incumbent" "' 1.5 " ", noticks labsize(large)) ylabel(-.3(.05)-.55,nogrid) title("Treatment Before Moderator", color(black)) yscale(noextend)  plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(8) saving(mexnoprimeate)

reg trust c.female_inc##c.corruption woman right center left if primed==1

reg evaluation c.female_inc##c.corruption woman right center left if primed==1

reg remove c.female_inc##c.corruption woman right center left if primed==1

reg popularity c.female_inc##c.corruption woman right center left if primed==1

margins, dydx(corruption) at(female_inc=(0(1)1))

marginsplot, x(female_inc) plot1(mcolor(black) connect(none)) ci1(lcolor(black) msize(vtiny)) ytitle("", height(7)) xtitle("") xlabel(-.5 " " 0 `" "Male" "Incumbent" "' 1 `" "Female" "Incumbent" "' 1.5 " ", noticks labsize(large)) ylabel(-.3(.05)-.55,nogrid) title("Treatment After Moderator", color(black) ) yscale(noextend)  plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(8) saving(mexprimeate)

reg popularity c.female_inc##c.corruption##i.primed woman right center left

* combing graphs by priming

graph combine mexnoprimeate.gph mexprimeate.gph, ycommon title(Mexico, size(vlarge)) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(14) iscale(1) saving(mexateprime)


* no interaction, male

reg trust c.female_inc##c.corruption right center left if primed==0 & woman==0

reg evaluation c.female_inc##c.corruption right center left if primed==0 & woman==0

reg remove c.female_inc##c.corruption right center left if primed==0 & woman==0

reg popularity c.female_inc##c.corruption right center left if primed==0 & woman==0

reg trust c.female_inc##c.corruption right center left if  primed==1 & woman==0

reg evaluation c.female_inc##c.corruption right center left if  primed==1 & woman==0

reg remove c.female_inc##c.corruption right center left if  primed==1 & woman==0

reg popularity c.female_inc##c.corruption right center left if  primed==1 & woman==0

reg popularity c.female_inc##c.corruption##i.primed right center left if woman==0


* no interaction, female

reg trust c.female_inc##c.corruption right center left if primed==0 & woman==1

reg evaluation c.female_inc##c.corruption right center left if primed==0 & woman==1

reg remove c.female_inc##c.corruption right center left if primed==0 & woman==1

reg popularity c.female_inc##c.corruption right center left if primed==0 & woman==1

reg trust c.female_inc##c.corruption right center left if primed==1 & woman==1

reg evaluation c.female_inc##c.corruption right center left if primed==1 & woman==1

reg remove c.female_inc##c.corruption right center left if primed==1 & woman==1

reg popularity c.female_inc##c.corruption right center left if primed==1 & woman==1

reg popularity c.female_inc##c.corruption##i.primed right center left if woman==1

* interacting male and female is not significant


* benevolent, full sample

reg trust c.female_inc##c.corruption##c.benevolent woman right center left if primed==0

reg evaluation c.female_inc##c.corruption##c.benevolent woman right center left if primed==0

reg remove c.female_inc##c.corruption##c.benevolent woman right center left if primed==0


reg popularity c.female_inc##c.corruption##c.benevolent woman right center left if primed==0

margins, dydx(corruption) at(female_inc=(0(1)1)  benevolent=(0(.25)1))

marginsplot, x(benevolent) plot(female_inc) plot1(mcolor(black) lcolor(black)) plot2(mcolor(gs8) lcolor(gs8)) ci1(lcolor(black) msize(vtiny)) ci2(lcolor(gs8) msize(vtiny)) title("Treatment Before Moderator", color(black)) ytitle("Treatment Effect", height(7)) xtitle("Benevolent Sexism", size(medlarge) height(5)) xlabel(0 "0" .25 ".25" .5 ".50" .75 ".75" 1 "1", noticks labsize(medium)) ylabel(0(.1)-.7, labsize(medium) nogrid) legend(col(2) order(1 "{stSans:Male Politician}" 2 "{stSans:Female Politician}") size(medium) ring(1) row(1)region(lstyle(none)) col(2) colg(7)) yscale(noextend) xscale(noextend) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(8) saving(mexnoprimehte)

power onemean .0147546 0, n(252) sd(.15)

reg trust c.female_inc##c.corruption##c.benevolent woman right center left if primed==1

reg evaluation c.female_inc##c.corruption##c.benevolent woman right center left if primed==1

reg remove c.female_inc##c.corruption##c.benevolent woman right center left if primed==1

reg popularity c.female_inc##c.corruption##c.benevolent woman right center left if primed==1

margins, dydx(corruption) at(female_inc=(0(1)1)  benevolent=(0(.25)1))

marginsplot, x(benevolent) plot(female_inc) plot1(mcolor(black) lcolor(black)) plot2(mcolor(gs8) lcolor(gs8)) ci1(lcolor(black) msize(vtiny)) ci2(lcolor(gs8) msize(vtiny)) title("Treatment After Moderator", color(black)) ytitle("Treatment Effect", height(7)) xtitle("Benevolent Sexism", size(medlarge) height(5)) xlabel(0 "0" .25 ".25" .5 ".50" .75 ".75" 1 "1", noticks labsize(medium)) ylabel(0(.1)-.7, labsize(medium) nogrid) legend(col(2) order(1 "{stSans:Male Politician}" 2 "{stSans:Female Politician}") size(medium) ring(1) row(1)region(lstyle(none)) col(2) colg(7)) yscale(noextend) xscale(noextend) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(8) saving(mexprimehte)

* combing graphs by priming

graph combine mexnoprimehte.gph mexprimehte.gph, ycommon title(Mexico, size(vlarge)) subtitle(Full Sample, span) plotregion(style(none)) graphregion(color(white)) ysize(8) xsize(14) saving(mexhteprime)

* benevolent, male

reg trust c.female_inc##c.corruption##c.benevolent right center left if primed==0 & woman==0

reg evaluation c.female_inc##c.corruption##c.benevolent right center left if primed==0 & woman==0

reg remove c.female_inc##c.corruption##c.benevolent right center left if primed==0 & woman==0

reg popularity c.female_inc##c.corruption##c.benevolent right center left if primed==0 & woman==0

reg trust c.female_inc##c.corruption##c.benevolent right center left if primed==1 & woman==0

reg evaluation c.female_inc##c.corruption##c.benevolent right center left if primed==1 & woman==0

reg remove c.female_inc##c.corruption##c.benevolent right center left if primed==1 & woman==0

reg popularity c.female_inc##c.corruption##c.benevolent right center left if primed==1 & woman==0

* benevolent, female

reg trust c.female_inc##c.corruption##c.benevolent right center left if primed==0 & woman==1

reg evaluation c.female_inc##c.corruption##c.benevolent right center left if primed==0 & woman==1

reg remove c.female_inc##c.corruption##c.benevolent right center left if primed==0 & woman==1

reg popularity c.female_inc##c.corruption##c.benevolent right center left if primed==0 & woman==1

reg trust c.female_inc##c.corruption##c.benevolent right center left if primed==1 & woman==1

reg evaluation c.female_inc##c.corruption##c.benevolent right center left if primed==1 & woman==1

reg remove c.female_inc##c.corruption##c.benevolent right center left if primed==1 & woman==1

reg popularity c.female_inc##c.corruption##c.benevolent right center left if primed==1 & woman==1


* menbetterleaders, full sample

reg trust c.female_inc##c.corruption##c.menbetterleaders woman right center left if primed==0

reg evaluation c.female_inc##c.corruption##c.menbetterleaders woman right center left if primed==0

reg remove c.female_inc##c.corruption##c.menbetterleaders woman right center left if primed==0

reg popularity c.female_inc##c.corruption##c.menbetterleaders woman right center left if primed==0

reg trust c.female_inc##c.corruption##c.menbetterleaders woman right center left if primed==1

reg evaluation c.female_inc##c.corruption##c.menbetterleaders woman right center left if primed==1

reg remove c.female_inc##c.corruption##c.menbetterleaders woman right center left if primed==1

reg popularity c.female_inc##c.corruption##c.menbetterleaders woman right center left if primed==1

* menbetterleaders, male

reg trust c.female_inc##c.corruption##c.menbetterleaders  right center left if primed==0 & woman==0

reg evaluation c.female_inc##c.corruption##c.menbetterleaders  right center left if primed==0 & woman==0

reg remove c.female_inc##c.corruption##c.menbetterleaders  right center left if primed==0 & woman==0

reg popularity c.female_inc##c.corruption##c.menbetterleaders  right center left if primed==0 & woman==0

reg trust c.female_inc##c.corruption##c.menbetterleaders  right center left if primed==1 & woman==0

reg evaluation c.female_inc##c.corruption##c.menbetterleaders  right center left if primed==1 & woman==0

reg remove c.female_inc##c.corruption##c.menbetterleaders  right center left if primed==1 & woman==0

reg popularity c.female_inc##c.corruption##c.menbetterleaders right center left if primed==1& woman==0

* menbetterleaders, female

reg trust c.female_inc##c.corruption##c.menbetterleaders right center left if primed==0 & woman==1

reg evaluation c.female_inc##c.corruption##c.menbetterleaders right center left if primed==0 & woman==1

reg remove c.female_inc##c.corruption##c.menbetterleaders right center left if primed==0 & woman==1

reg popularity c.female_inc##c.corruption##c.menbetterleaders right center left if primed==0 & woman==1

reg trust c.female_inc##c.corruption##c.menbetterleaders right center left if primed==1& woman==1

reg evaluation c.female_inc##c.corruption##c.menbetterleaders right center left if primed==1& woman==1

reg remove c.female_inc##c.corruption##c.menbetterleaders right center left if primed==1& woman==1

reg popularity c.female_inc##c.corruption##c.menbetterleaders right center left if primed==1& woman==1
